I have a project and I want to convert it to multi-threaded application. What are the things that can be done to make it a multi threaded application
List out things to be done to convert into multithreaded application
e.g mutex lock on shared variables.
I was not able to find a question which list all those under single hood.
project is in C
Single threaded application need not be concerned about being thread safe.
This issue arises when you have multiple threads which are trying to access a commonly shared resource. At that time, you must be concerned.
So, no need to worry.
EDIT (after question been edited ) :
You need to go through the following links.
Single threaded to multithreaded application
Single threaded to multithreaded application - What we need to consider ?
Advice - Single threaded to multithreaded application
Also a good advice for converting single to multithreaded application.Check out.
Single threaded -> Multithreaded application :: Good advice.
The big issue is that, in general, when designing your application it is very difficult to choose single thread and then later on add multi-threading. The choice is fundamental to the design idioms you are going to strive towards. Here's a brief but poor guide of some of the things you should be paying attention towards and how to modify your code (note, none of these are set in stone, there's always a way around):
Remove all mutable global variables. I'd say this goes for single threaded applications too but that's just me.
Add "const" to as many variables as you can as a first pass to decide where there are state changes and take notes from the compilation errors. This is not to say "turn all your variables to const." It is just s simple hack to figure out where your problem areas are going to be.
For those items which are mutable and which will be shared (that is, you can't leave them as const without compilation warnings) put locks around them. Each lock should be logged.
Next, introduce your threads. You're probably about to suffer a lot of deadlocks, livelocks, race conditions, and what not as your single threaded application made assumptions about the way and order your application would run.
Start by paring away unneeded locks. That is, look to the mutable state which isn't shared amongst your threads. Those locks are superfluous and need to go.
Next, study your code. At this point, determining where your threaded issues are is more art than science. Although, there are decent principals about how to go about this, that's about all I can say.
If that sounds like too much effort, it's time to look towards the Actor model for concurrency. This would be akin to creating several different applications which call one another through a message passing scheme. I find that Actors are not only intuitive but also massively friendly to determining where and how you might encounter threading issues. When setting up Actors, it's almost impossible not to think about all the "what ifs."
Personally, when dealing with a single threaded to multi threaded conversion, I do as little as possible to meet project goals. It's just safer.
This depends very heavily on exactly how you intend to use threads. What does your program do? Where do you want to use threads? What will those threads be doing?
You will need to figure out what resources these threads will be sharing, and apply appropriate locking. Since you're starting with a single-threaded application, it's a good idea to minimize the shared resources to make porting easier. For example, if you have a single GUI thread right now, and need to do some complex computations in multiple threads, spawn those threads, but don't have them directly touch any data for the GUI - instead, send a asynchronous message to the GUI thread (how you do this depends on the OS and GUI library) and have it handle any changes to GUI-thread data in a serialized fashion on the GUI thread itself.
As general advice, don't simply add threads willy-nilly. You should know exactly which variables and data structures are shared between threads, where they are accessed, and why. And you should be keeping said sharing to the minimum.
Without a much more detailed description of your application, it's nearly impossible to give you a complete answer.
It will be a good idea to give some insight in your understanding of threading aswell.
However, the most important is that each time a global variable is accessed or a pointer is used, there's a good chance you'll need to do that inside of a mutex.
This wikipedia page should be a good start : http://en.wikipedia.org/wiki/Thread_safety
Related
I want to write a simple multiplayer game as part of my C++ learning project.
So I thought, since I am at it, I would like to do it properly, as opposed to just getting-it-done.
If I understood correctly: Apache uses a Thread-per-connection architecture, while nginx uses an event-loop and then dedicates a worker [x] for the incoming connection. I guess nginx is wiser, since it supports a higher concurrency level. Right?
I have also come across this clever analogy, but I am not sure if it could be applied to my situation. The analogy also seems to be very idealist. I have rarely seen my computer run at 100% CPU (even with a umptillion Chrome tabs open, Photoshop and what-not running simultaneously)
Also, I have come across a SO post (somehow it vanished from my history) where a user asked how many threads they should use, and one of the answers was that it's perfectly acceptable to have around 700, even up to 10,000 threads. This question was related to JVM, though.
So, let's estimate a fictional user-base of around 5,000 users. Which approach should would be the "most concurrent" one?
A reactor pattern running everything in a single thread.
A reactor pattern with a thread-pool (approximately, how big do you suggest the thread pool should be?
Creating a thread per connection and then destroying the thread the connection closes.
I admit option 2 sounds like the best solution to me, but I am very green in all of this, so I might be a bit naive and missing some obvious flaw. Also, it sounds like it could be fairly difficult to implement.
PS: I am considering using POCO C++ Libraries. Suggesting any alternative libraries (like boost) is fine with me. However, many say POCO's library is very clean and easy to understand. So, I would preferably use that one, so I can learn about the hows of what I'm using.
Reactive Applications certainly scale better, when they are written correctly. This means
Never blocking in a reactive thread:
Any blocking will seriously degrade the performance of you server, you typically use a small number of reactive threads, so blocking can also quickly cause deadlock.
No mutexs since these can block, so no shared mutable state. If you require shared state you will have to wrap it with an actor or similar so only one thread has access to the state.
All work in the reactive threads should be cpu bound
All IO has to be asynchronous or be performed in a different thread pool and the results feed back into the reactor.
This means using either futures or callbacks to process replies, this style of code can quickly become unmaintainable if you are not used to it and disciplined.
All work in the reactive threads should be small
To maintain responsiveness of the server all tasks in the reactor must be small (bounded by time)
On an 8 core machine you cannot cannot allow 8 long tasks arrive at the same time because no other work will start until they are complete
If a tasks could take a long time it must be broken up (cooperative multitasking)
Tasks in reactive applications are scheduled by the application not the operating system, that is why they can be faster and use less memory. When you write a Reactive application you are saying that you know the problem domain so well that you can organise and schedule this type of work better than the operating system can schedule threads doing the same work in a blocking fashion.
I am a big fan of reactive architectures but they come with costs. I am not sure I would write my first c++ application as reactive, I normally try to learn one thing at a time.
If you decide to use a reactive architecture use a good framework that will help you design and structure your code or you will end up with spaghetti. Things to look for are:
What is the unit of work?
How easy is it to add new work? can it only come in from an external event (eg network request)
How easy is it to break work up into smaller chunks?
How easy is it to process the results of this work?
How easy is it to move blocking code to another thread pool and still process the results?
I cannot recommend a C++ library for this, I now do my server development in Scala and Akka which provide all of this with an excellent composable futures library to keep the code clean.
Best of luck learning C++ and with which ever choice you make.
Option 2 will most efficiently occupy your hardware. Here is the classic article, ten years old but still good.
http://www.kegel.com/c10k.html
The best library combination these days for structuring an application with concurrency and asynchronous waiting is Boost Thread plus Boost ASIO. You could also try a C++11 std thread library, and std mutex (but Boost ASIO is better than mutexes in a lot of cases, just always callback to the same thread and you don't need protected regions). Stay away from std future, cause it's broken:
http://bartoszmilewski.com/2009/03/03/broken-promises-c0x-futures/
The optimal number of threads in the thread pool is one thread per CPU core. 8 cores -> 8 threads. Plus maybe a few extra, if you think it's possible that your threadpool threads might call blocking operations sometimes.
FWIW, Poco supports option 2 (ParallelReactor) since version 1.5.1
I think that option 2 is the best one. As for tuning of the pool size, I think the pool should be adaptive. It should be able to spawn more threads (with some high hard limit) and remove excessive threads in times of low activity.
as the analogy you linked to (and it's comments) suggest. this is somewhat application dependent. now what you are building here is a game server. let's analyze that.
game servers (generally) do a lot of I/O and relatively few calculations, so they are far from 100% CPU applications.
on the other hand they also usually change values in some database (a "game world" model). all players create reads and writes to this database. which is exactly the intersection problem in the analogy.
so while you may gain some from handling the I/O in separate threads, you will also lose from having separate threads accessing the same database and waiting for its locks.
so either option 1 or 2 are acceptable in your situation. for scalability reasons I would not recommend option 3.
Is it ok to check the current thread inside a function?
For example if some non-thread safe data structure is only altered by one thread, and there is a function which is called by multiple threads, it would be useful to have separate code paths depending on the current thread. If the current thread is the one that alters the data structure, it is ok to alter the data structure directly in the function. However, if the current thread is some other thread, the actual altering would have to be delayed, so that it is performed when it is safe to perform the operation.
Or, would it be better to use some boolean which is given as a parameter to the function to separate the different code paths?
Or do something totally different?
What do you think?
You are not making all too much sense. You said a non-thread safe data structure is only ever altered by one thread, but in the next sentence you talk about delaying any changes made to that data structure by other threads. Make up your mind.
In general, I'd suggest wrapping the access to the data structure up with a critical section, or mutex.
It's possible to use such animals as reader/writer locks to differentiate between readers and writers of datastructures but the performance advantage for typical cases usually wont merit the additional complexity associated with their use.
From the way your question is stated, I'm guessing you're fairly new to multithreaded development. I highly suggest sticking with the simplist and most commonly used approaches for ensuring data integrity (most books/articles you readon the issue will mention the same uses for mutexes/critical sections). Multithreaded development is extremely easy to get wrong and can be difficult to debug. Also, what seems like the "optimal" solution very often doesn't buy you the huge performance benefit you might think. It's usually best to implement the simplist approach that will work then worry about optimizing it after the fact.
There is a trick that could work in case, as you said, the other threads will only make changes only once in a while, although it is still rather hackish:
make sure your "master" thread can't be interrupted by the other ones (higher priority, non fair scheduling)
check your thread
if "master", just change
if other, put off scheduling, if needed by putting off interrupts, make change, reinstall scheduling
really test to see whether there are no issues in your setup.
As you can see, if requirements change a little bit, this could turn out worse than using normal locks.
As mentioned, the simplest solution when two threads need access to the same data is to use some synchronization mechanism (i.e. critical section or mutex).
If you already have synchronization in your design try to reuse it (if possible) instead of adding more. For example, if the main thread receives its work from a synchronized queue you might be able to have thread 2 queue the data structure update. The main thread will pick up the request and can update it without additional synchronization.
The queuing concept can be hidden from the rest of the design through the Active Object pattern. The activ object may also be able to publish the data structure changes through the Observer pattern to other interested threads.
This is my follow up to the previous post on memory management issues. The following are the issues I know.
1)data races (atomicity violations and data corruption)
2)ordering problems
3)misusing of locks leading to dead locks
4)heisenbugs
Any other issues with multi threading ? How to solve them ?
Eric's list of four issues is pretty much spot on. But debugging these issues is tough.
For deadlock, I've always favored "leveled locks". Essentially you give each type of lock a level number. And then require that a thread aquire locks that are monotonic.
To do leveled locks, you can declare a structure like this:
typedef struct {
os_mutex actual_lock;
int level;
my_lock *prev_lock_in_thread;
} my_lock_struct;
static __tls my_lock_struct *last_lock_in_thread;
void my_lock_aquire(int level, *my_lock_struct lock) {
if (last_lock_in_thread != NULL) assert(last_lock_in_thread->level < level)
os_lock_acquire(lock->actual_lock)
lock->level = level
lock->prev_lock_in_thread = last_lock_in_thread
last_lock_in_thread = lock
}
What's cool about leveled locks is the possibility of deadlock causes an assertion. And with some extra magic with FUNC and LINE you know exactly what badness your thread did.
For data races and lack of synchronization, the current situation is pretty poor. There are static tools that try to identify issues. But false positives are high.
The company I work for ( http://www.corensic.com ) has a new product called Jinx that actively looks for cases where race conditions can be exposed. This is done by using virtualization technology to control the interleaving of threads on the various CPUs and zooming in on communication between CPUs.
Check it out. You probably have a few more days to download the Beta for free.
Jinx is particularly good at finding bugs in lock free data structures. It also does very well at finding other race conditions. What's cool is that there are no false positives. If your code testing gets close to a race condition, Jinx helps the code go down the bad path. But if the bad path doesn't exist, you won't be given false warnings.
Unfortunately there's no good pill that helps automatically solve most/all threading issues. Even unit tests that work so well on single-threaded pieces of code may never detect an extremely subtle race condition.
One thing that will help is keeping the thread-interaction data encapsulated in objects. The smaller the interface/scope of the object, the easier it will be to detect errors in review (and possibly testing, but race conditions can be a pain to detect in test cases). By keeping a simple interface that can be used, clients that use the interface will also be correct just by default. By building up a bigger system from lots of smaller pieces (only a handful of which actually do thread-interaction), you can go a long way towards averting threading errors in the first place.
The four most common problems with theading are
1-Deadlock
2-Livelock
3-Race Conditions
4-Starvation
How to solve [issues with multi threading]?
A good way to "debug" MT applications is through logging. A good logging library with extensive filtering options makes it easier. Of course, logging itself influences the timing, so you still can have "heisenbugs", but it's much less likely than when you're actuall breaking into the debugger.
Prepare and plan for that. Include a good logging facility into your application from the start.
Make your threads as simple as possible.
Try not to use global variables. Global constants (actual constants that never change) is fine. When you do need to use global or shared variables you need to protect them with some type of mutex/lock (semaphore, monitor, ...).
Make sure that you actually understand what how your mutexes work. There are a few different implementations which can work differently.
Try to organize your code so that the critical sections (places where you hold some type of lock(s) ) are as quick as possible. Be aware that some functions may block (sleep or wait on something and keep the OS from allowing that thread to continue running for some time). Do not use these while holding any locks (unless absolutely necessary or during debugging as it can sometimes show other bugs).
Try to understand what more threads actually does for you. Blindly throwing more threads at a problem is very often going to make things worse. Different threads compete for the CPU and for locks.
Deadlock avoidance requires planning. Try to avoid having to acquire more than one lock at a time. If this is unavoidable decide on an ordering you will use to acquire and release the locks for all threads. Make sure you know what deadlock really means.
Debugging multi-threaded or distributed applications is difficult. If you can do most of the debugging in a single threaded environment (maybe even just forcing other threads to sleep) then you can try to eliminate non-threading centric bugs before jumping into multi-threaded debugging.
Always think about what the other threads might be up to. Comment this in your code. If you are doing something a certain way because you know that at that time no other thread should be accessing a certain resource write a big comment saying so.
You may want to wrap calls to mutex locks/unlocks in other functions like:
int my_lock_get(lock_type lock, const char * file, unsigned line, const char * msg) {
thread_id_type me = this_thread();
logf("%u\t%s (%u)\t%s:%u\t%s\t%s\n", time_now(), thread_name(me), me, "get", msg);
lock_get(lock);
logf("%u\t%s (%u)\t%s:%u\t%s\t%s\n", time_now(), thread_name(me), me, "in", msg);
}
And a similar version for unlock. Note, the functions and types used in this are all made up and not overly based on any one API.
Using something like this you can come back if there is an error and use a perl script or something like it to run queries on your logs to examine where things went wrong (matching up locks and unlocks, for instance).
Note that your print or logging functionality may need to have locks around it as well. Many libraries already have this built in, but not all do. These locks need to not use the printing version of the lock_[get|release] functions or you'll have infinite recursion.
Beware of global variables even if
they are const, in particular in
C++. Only POD that are statically
initialized "à la" C are good here.
As soon as a run-time constructor
comes into play, be extremely
careful. AFAIR initialization order
of variables with static linkage that are in
different compilation units are
called in an undefined order. Maybe
C++ classes that initialize all
their members properly and have an
empty function body, could be ok
nowadays, but I once had a bad
experience with that, too.
This is one of the reason why on the
POSIX side pthread_mutex_t is much
easier to program than sem_t: it
has a static initializer
PTHREAD_MUTEX_INITIALIZER.
Keep critical sections as short as
possible, for two reasons: it might
be more efficient at the end, but
more importantly it is easier to
maintain and to debug.
A critical section should never be
longer that a screen, including the
locking and unlocking that is needed
to protect it, and including the
comments and assertions that help
the reader to understand what is
happening.
Start implementing critical sections
very rigidly maybe with one global
lock for them all, and relax the
constraints afterwards.
Logging might is difficult if many
threads start to write at the same
time. If every thread does a
reasonable amount of work try to
have them each write a file of their
own, such that they don't interlock
each other.
But beware, logging changes behavior
of code. This can be bad when bugs
disappear, or beneficial when bugs
appear that you otherwise wouldn't
have noticed.
To make a post-mortem analysis of
such a mess you have to have
accurate timestamps on each line
such that all the files can be
merged and give you a coherent view
of the execution.
-> Add priority inversion to that list.
As another poster eluded to, log files are wonderful things. For deadlocks, using a LogLock instead of a Lock can help pinpoint when you entities stop working. That is, once you know you've got a deadlock, the log will tell you when and where locks were instantiated and released. This can be enormously helpful in tracking these things down.
I've found that race conditions when using an Actor model following the same message->confirm->confirm received style seem to disappear. That said, YMMV.
I have never come across multithreading but I hear about it everywhere. What should I know about it and when should I use it? I code mainly in c++.
Mostly, you will need to learn about MT libraries on OS on which your application needs to run. Until and unless C++0x becomes a reality (which is a long way as it looks now), there is no support from the language proper or the standard library for threads. I suggest you take a look at the POSIX standard pthreads library for *nix and Windows threads to get started.
This is my opinion, but the biggest issue with multithreading is that it is difficult. I don't mean that from an experienced programmer point of view, I mean it conceptually. There really are a lot of difficult concurrency problems that appear once you dive into parallel programming. This is well known, and there are many approaches taken to make concurrency easier for the application developer. Functional languages have become a lot more popular because of their lack of side effects and idempotency. Some vendors choose to hide the concurrency behind API's (like Apple's Core Animation).
Multitheaded programs can see some huge gains in performance (both in user perception and actual amount of work done), but you do have to spend time to understand the interactions that your code and data structures make.
MSDN Multithreading for Rookies article is probably worth reading. Being from Microsoft, it's written in terms of what Microsoft OSes support(ed in 1993), but most of the basic ideas apply equally to other systems, with suitable renaming of functions and such.
That is a huge subject.
A few points...
With multi-core, the importance of multi-threading is now huge. If you aren't multithreading, you aren't getting the full performance capability of the machine.
Multi-threading is hard. Communicating and synchronization between threads is tricky to get right. Problems are often intermittent, hard to diagnose, and if the design isn't right for multi-threading, hard to fix.
Multi-threading is currently mostly non-portable and platform specific.
There are portable libraries with wrappers around threading APIs. Boost is one. wxWidgets (mainly a GUI library) is another. It can be done reasonably portably, but you won't have all the options you get from platform-specific APIs.
I've got an introduction to multithreading that you might find useful.
In this article there isn't a single
line of code and it's not aimed at
teaching the intricacies of
multithreaded programming in any given
programming language but to give a
short introduction, focusing primarily
on how and especially why and when
multithreaded programming would be
useful.
Here's a link to a good tutorial on POSIX threads programming (with diagrams) to get you started. While this tutorial is pthread specific, many of the concepts transfer to other systems.
To understand more about when to use threads, it helps to have a basic understanding of parallel programming. Here's a link to a tutorial on the very basics of parallel computing intended for those who are just becoming acquainted with the subject.
The other replies covered the how part, I'll briefly mention when to use multithreading.
The main alternative to multithreading is using a timer. Consider for example that you need to update a little label on your form with the existence of a file. If the file exists, you need to draw a special icon or something. Now if you use a timer with a low timeout, you can achieve basically the same thing, a function that polls if the file exists very frequently and updates your ui. No extra hassle.
But your function is doing a lot of unnecessary work, isn't it. The OS provides a "hey this file has been created" primitive that puts your thread to sleep until your file is ready. Obviously you can't use this from the ui thread or your entire application would freeze, so instead you spawn a new thread and set it to wait on the file creation event.
Now your application is using as little cpu as possible because of the fact that threads can wait on events (be it with mutexes or events). Say your file is ready however. You can't update your ui from different threads because all hell would break loose if 2 threads try to change the same bit of memory at the same time. In fact this is so bad that windows flat out rejects your attempts to do it at all.
So now you need either a synchronization mechanism of sorts to communicate with the ui one after the other (serially) so you don't step on eachother's toes, but you can't code the main thread part because the ui loop is hidden deep inside windows.
The other alternative is to use another way to communicate between threads. In this case, you might use PostMessage to post a message to the main ui loop that the file has been found and to do its job.
Now if your work can't be waited upon and can't be split nicely into little bits (for use in a short-timeout timer), all you have left is another thread and all the synchronization issues that arise from it.
It might be worth it. Or it might bite you in the ass after days and days, potentially weeks, of debugging the odd race condition you missed. It might pay off to spend a long time first to try to split it up into little bits for use with a timer. Even if you can't, the few cases where you can will outweigh the time cost.
You should know that it's hard. Some people think it's impossibly hard, that there's no practical way to verify that a program is thread safe. Dr. Hipp, author of sqlite, states that thread are evil. This article covers the problems with threads in detail.
The Chrome browser uses processes instead of threads, and tools like Stackless Python avoid hardware-supported threads in favor of interpreter-supported "micro-threads". Even things like web servers, where you'd think threading would be a perfect fit, and moving towards event driven architectures.
I myself wouldn't say it's impossible: many people have tried and succeeded. But there's no doubt writting production quality multi-threaded code is really hard. Successful multi-threaded applications tend to use only a few, predetermined threads with just a few carefully analyzed points of communication. For example a game with just two threads, physics and rendering, or a GUI app with a UI thread and background thread, and nothing else. A program that's spawning and joining threads throughout the code base will certainly have many impossible-to-find intermittent bugs.
It's particularly hard in C++, for two reasons:
the current version of the standard doesn't mention threads at all. All threading libraries and platform and implementation specific.
The scope of what's considered an atomic operation is rather narrow compared to a language like Java.
cross-platform libraries like boost Threads mitigate this somewhat. The future C++0x will introduce some threading support. But boost also has good interprocess communication support you could use to avoid threads altogether.
If you know nothing else about threading than that it's hard and should be treated with respect, than you know more than 99% of programmers.
If after all that, you're still interested in starting down the long hard road towards being able to write a multi-threaded C++ program that won't segfault at random, then I recommend starting with Boost threads. They're well documented, high level, and work cross platform. The concepts (mutexes, locks, futures) are the same few key concepts present in all threading libraries.
I have some long-running operations that number in the hundreds. At the moment they are each on their own thread. My main goal in using threads is not to speed these operations up. The more important thing in this case is that they appear to run simultaneously.
I'm aware of cooperative multitasking and fibers. However, I'm trying to avoid anything that would require touching the code in the operations, e.g. peppering them with things like yieldToScheduler(). I also don't want to prescribe that these routines be stylized to be coded to emit queues of bite-sized task items...I want to treat them as black boxes.
For the moment I can live with these downsides:
Maximum # of threads tend to be O(1000)
Cost per thread is O(1MB)
To address the bad cache performance due to context-switches, I did have the idea of a timer which would juggle the priorities such that only idealThreadCount() threads were ever at Normal priority, with all the rest set to Idle. This would let me widen the timeslices, which would mean fewer context switches and still be okay for my purposes.
Question #1: Is that a good idea at all? One certain downside is it won't work on Linux (docs say no QThread::setPriority() there).
Question #2: Any other ideas or approaches? Is QtConcurrent thinking about this scenario?
(Some related reading: how-many-threads-does-it-take-to-make-them-a-bad-choice, many-threads-or-as-few-threads-as-possible, maximum-number-of-threads-per-process-in-linux)
IMHO, this is a very bad idea. If I were you, I would try really, really hard to find another way to do this. You're combining two really bad ideas: creating a truck load of threads, and messing with thread priorities.
You mention that these operations only need to appear to run simultaneously. So why not try to find a way to make them appear to run simultaneously, without literally running them simultaneously?
It's been 6 months, so I'm going to close this.
Firstly I'll say that threads serve more than one purpose. One is speedup...and a lot of people are focusing on that in the era of multi-core machines. But another is concurrency, which can be desirable even if it slows the system down when taken as a whole. Yet concurrency can be achieved using mechanisms more lightweight than threads, although it may complicate the code.
So this is just one of those situations where the tradeoff of programmer convenience against user experience must be tuned to fit the target environment. It's how Google's approach to a process-per-tab with Chrome would have been ill-advised in the era of Mosaic (even if process isolation was preferable with all else being equal). If the OS, memory, and CPU couldn't give a good browsing experience...they wouldn't do it that way now.
Similarly, creating a lot of threads when there are independent operations you want to be concurrent saves you the trouble of sticking in your own scheduler and yield() operations. It may be the cleanest way to express the code, but if it chokes the target environment then something different needs to be done.
So I think I'll settle on the idea that in the future when our hardware is better than it is today, we'll probably not have to worry about how many threads we make. But for now I'll take it on a case-by-case basis. i.e. If I have 100 of concurrent task class A, and 10 of concurrent task class B, and 3 of concurrent task class C... then switching A to a fiber-based solution and giving it a pool of a few threads is probably worth the extra complication.